Paper
6 December 2011 Detecting skin colors under varying illumination
Leyuan Liu, Rui Huang, Saiyong Yang, Nong Sang
Author Affiliations +
Proceedings Volume 8004, MIPPR 2011: Pattern Recognition and Computer Vision; 80040N (2011) https://doi.org/10.1117/12.901776
Event: Seventh International Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR2011), 2011, Guilin, China
Abstract
Skin color has been used as an important cue for various human related computer vision applications. However, detecting skin colors under varying illumination is a challenging task, as the appearance of skin in an image highly depends on the illumination under which the image was taken. To this end, a method for detecting skin colors under varying illumination is proposed in this paper. First, spatial illumination variation is identified and the images are segmented into different regions with different illumination. Each illumination region of color images are corrected base on the illuminant estimated by a local edge-based color constancy algorithm. Then, the corrected images are transformed into a color-space, where statistical results on a skin dataset show that the skin color cluster and non-skin color clusters are separated. Finally, the skin colors are modeled under Bayesian decision framework and classified from non-skin colors. The experimental results show that the proposed method is robust to illumination variations.
© (2011) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Leyuan Liu, Rui Huang, Saiyong Yang, and Nong Sang "Detecting skin colors under varying illumination", Proc. SPIE 8004, MIPPR 2011: Pattern Recognition and Computer Vision, 80040N (6 December 2011); https://doi.org/10.1117/12.901776
Lens.org Logo
CITATIONS
Cited by 4 scholarly publications.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Skin

Image segmentation

RGB color model

Detection and tracking algorithms

Facial recognition systems

Computer vision technology

Machine vision

RELATED CONTENT

Saliency detection based on manifold learning
Proceedings of SPIE (October 27 2013)
A region finding method to remove the noise from the...
Proceedings of SPIE (December 08 2015)
Pixel and spatial mechanisms of color constancy
Proceedings of SPIE (January 18 2010)

Back to Top